diff --git a/colossalai/fx/tracer/meta_patch/patched_function.py b/colossalai/fx/tracer/meta_patch/patched_function.py
index a9ddda8e8..dd6312ccb 100644
--- a/colossalai/fx/tracer/meta_patch/patched_function.py
+++ b/colossalai/fx/tracer/meta_patch/patched_function.py
@@ -218,3 +218,8 @@ def torch_cat(tensors, dim=None, axis=None, *, out=None):
     concatenated_dim = sum(shape[dim] for shape in shapes)
     final_shape = shape[:dim] + [concatenated_dim] + shape[dim + 1:]
     return torch.empty(final_shape, device="meta")
+
+
+@meta_patched_function.register(torch.roll)
+def torch_roll(input, shifts, dims=None):
+    return torch.empty(input.shape, device='meta')
diff --git a/colossalai/fx/tracer/meta_patch/patched_module.py b/colossalai/fx/tracer/meta_patch/patched_module.py
index 2e2cedfe2..787e7e68b 100644
--- a/colossalai/fx/tracer/meta_patch/patched_module.py
+++ b/colossalai/fx/tracer/meta_patch/patched_module.py
@@ -249,6 +249,34 @@ def torch_nn_maxpool3d(self, input):
     return torch.empty(result_shape, device='meta')
 
 
+@meta_patched_module.register(torch.nn.AdaptiveAvgPool1d)
+@meta_patched_module.register(torch.nn.AdaptiveMaxPool1d)
+def torch_nn_adapative_pooling_1d(self, input):
+    result_shape = input.shape[:-1] + (self.output_size,)
+    return torch.empty(result_shape, device='meta')
+
+
+@meta_patched_module.register(torch.nn.AdaptiveAvgPool2d)
+@meta_patched_module.register(torch.nn.AdaptiveMaxPool2d)
+def torch_nn_adapative_pooling_2d(self, input):
+    result_shape = input.shape[:-2] + (
+        self.output_size,
+        self.output_size,
+    )
+    return torch.empty(result_shape, device='meta')
+
+
+@meta_patched_module.register(torch.nn.AdaptiveAvgPool3d)
+@meta_patched_module.register(torch.nn.AdaptiveMaxPool3d)
+def torch_nn_adapative_pooling_3d(self, input):
+    result_shape = input.shape[:-3] + (
+        self.output_size,
+        self.output_size,
+        self.output_size,
+    )
+    return torch.empty(result_shape, device='meta')
+
+
 @meta_patched_module.register(torch.nn.ReLU)
 @meta_patched_module.register(torch.nn.ReLU6)
 def torch_nn_func_relu(self, input):
diff --git a/tests/test_fx/test_tracer/test_timm_model/test_timm_model.py b/tests/test_fx/test_tracer/test_timm_model/test_timm_model.py
index b69900d0b..7df0b2e6c 100644
--- a/tests/test_fx/test_tracer/test_timm_model/test_timm_model.py
+++ b/tests/test_fx/test_tracer/test_timm_model/test_timm_model.py
@@ -63,14 +63,8 @@ def test_timm_models_with_control_flow():
     torch.backends.cudnn.deterministic = True
 
     MODEL_LIST_WITH_CONTROL_FLOW = [
-        tm.convnext.convnext_base,
-        tm.vgg.vgg11,
-        tm.dpn.dpn68,
-        tm.densenet.densenet121,
-        tm.rexnet.rexnet_100,
-
-    # not traceable
-    # tm.swin_transformer.swin_base_patch4_window7_224
+        tm.convnext.convnext_base, tm.vgg.vgg11, tm.dpn.dpn68, tm.densenet.densenet121, tm.rexnet.rexnet_100,
+        tm.swin_transformer.swin_base_patch4_window7_224
     ]
 
     tracer = ColoTracer()